Instructions to use logic65/whittle-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use logic65/whittle-dev with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf logic65/whittle-dev:Q8_0
# Run inference directly in the terminal:
llama cli -hf logic65/whittle-dev:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf logic65/whittle-dev:Q8_0
# Run inference directly in the terminal:
llama cli -hf logic65/whittle-dev:Q8_0

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf logic65/whittle-dev:Q8_0
# Run inference directly in the terminal:
./build/bin/llama cli -hf logic65/whittle-dev:Q8_0

Use Docker

docker model run hf.co/logic65/whittle-dev:Q8_0

Llama new
LM Studio
Jan
Ollama
How to use logic65/whittle-dev with Ollama:
```
ollama run hf.co/logic65/whittle-dev:Q8_0
```
Unsloth Desktop

How to use logic65/whittle-dev with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf logic65/whittle-dev:Q8_0

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "logic65/whittle-dev:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use logic65/whittle-dev with Docker Model Runner:
```
docker model run hf.co/logic65/whittle-dev:Q8_0
```

Lemonade

How to use logic65/whittle-dev with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull logic65/whittle-dev:Q8_0

Run and chat with the model

lemonade run user.whittle-dev-Q8_0

List all available models

lemonade list

Hermes Agent

How to use logic65/whittle-dev with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf logic65/whittle-dev:Q8_0

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default logic65/whittle-dev:Q8_0

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use logic65/whittle-dev with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf logic65/whittle-dev:Q8_0

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "logic65/whittle-dev:Q8_0" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

logic65 commited on Sep 19

Commit

7057553

verified ·

1 Parent(s): 0c462b8

gguf ladder log

Browse files

Files changed (1) hide show

tbl1/eval/gguf_35b_v4.log +3 -0

tbl1/eval/gguf_35b_v4.log CHANGED Viewed

@@ -13,3 +13,6 @@
 10:28:26 Q3_K_M attempt 1 (plain) free 115 GB
 10:29:01 Q3_K_M ok: llama_quantize: quantize time = 35633.29 ms | llama_quantize:    total time = 35633.29 ms
 10:35:29 Q3_K_M 16.7 GB uploaded

 10:28:26 Q3_K_M attempt 1 (plain) free 115 GB
 10:29:01 Q3_K_M ok: llama_quantize: quantize time = 35633.29 ms | llama_quantize:    total time = 35633.29 ms
 10:35:29 Q3_K_M 16.7 GB uploaded
+10:35:32 LADDER: ['Whittle-Qwen-3.8-35B-A3B-Q3_K_M.gguf', 'Whittle-Qwen-3.8-35B-A3B-Q4_K_M.gguf', 'Whittle-Qwen-3.8-35B-A3B-Q5_K_M.gguf', 'Whittle-Qwen-3.8-35B-A3B-Q6_K.gguf', 'Whittle-Qwen-3.8-35B-A3B-Q8_0.gguf']
+10:35:32 SIZES {"Q8_0": 37.8, "Q6_K": 29.3, "Q5_K_M": 25.1, "Q4_K_M": 21.3, "Q3_K_M": 16.7}
+10:35:32 GGUF_35B DONE